Purpose
The Division of Cancer Control and Population Sciences (DCCPS) at the National Cancer Institute (NCI) announces this notice to encourage NCI-funded investigators to apply for administrative supplement funds to support research leveraging novel data science approaches to address integration of modifiable risk factors on cancer outcomes. The goal of the administrative supplement is to support the development and novel use of computational models for analyzing the joint effects of three or more temporally co-occurring modifiable risk factors on cancer outcomes.
Definitions
- Modifiable Risk Factors - Behaviors and/or exposures that can be changed (e.g., modified) to raise or lower a person's risk of developing cancer. Examples of modifiable risk factors include but are not limited to diet/nutrition, physical activity/inactivity, sedentary behavior, sleep, tobacco use, vaping, cannabis use, alcohol use, sun exposure, and microplastics exposure.
- Cancer Outcomes - For the purposes of this announcement, "cancer outcomes" include but are not limited to cancer risk reduction, early-onset cancer incidence, treatment factors, symptom management, and survivorship outcomes. The investigator-identified cancer outcome must be scientifically justified.
- Temporal Data - Data collected within a common temporal window or time period, often defined as a 24-hour period. Applicants may define a temporal window greater than 24-hours if scientifically justified.
- Novel Computational Models - For the purposes of this announcement, "novel computational models" are defined as analytic approaches and algorithms designed to simultaneously model and examine multiple, interdependent risk factors, leveraging advanced statistical, machine learning, and/or data integration techniques to capture complex interactions, dynamic relationships, and time-varying effects that occur within multidimensional temporal data.
Background
Up to 50% of cancers are attributable to modifiable risk factors such as poor sleep hygiene, physical inactivity, poor diet, tobacco use, and alcohol use. Notably, the prevalence of early-onset cancers has been rising, and research suggests that modifiable risk factors may also contribute significantly to this trend. These modifiable risk factors do not occur in isolation, with individuals often engaging in multiple behaviors, which may interact in complex ways, amplifying or mitigating health effects. Therefore, examining these behaviors in isolation fails to capture the full picture of their combined influence on cancer risk.
To address this gap, innovative computational modeling approaches to assess the joint effects of multiple temporally co-occurring modifiable risk factors on cancer outcomes are needed. Recent technological advances provide greater opportunities to collect temporally co-occurring data. For example, wearable devices that measure behaviors and exposures are becoming increasingly available, innovative methods can combine self-reported behavior (e.g., type, dose, duration) with device-based recordings (e.g., image, geospatial, and/or timestamp data), and real-world data sources that contain emerging and existing cancer risk factors are becoming widespread. However, traditional statistical approaches, such as multiple regression, are limited in their ability to capture the complex interactions, dynamic relationships, and time-varying effects that occur within multidimensional temporal data. To account for these complexities, new modeling approaches are needed, such as isotemporal substitution modeling, structural equation modeling, and machine learning methods.
Research Objectives
This administrative supplement allows currently funded NCI extramural investigators to develop and apply novel computational models that analyze the joint effects of three or more temporally co-occurring modifiable risk factors on cancer outcomes. Applicants must clearly demonstrate adequate access to temporal data at the individual level for each risk factor whether it be via existing data, integration through data linkages, and/or in combination with synthetic data. Modifiable risk factor data collected outside of the standard 24-hour temporal window must be scientifically justified.
Applications are encouraged across study designs and populations. Applications focusing on high-risk, understudied, and/or underserved cancer populations, including but not limited to individuals with early-onset cancers, rare cancers, pediatric cancer survivors, older cancer patients with comorbidities, and rural patient communities, are encouraged.
Modifiable risk factors can be collected through different tools and approaches, including but not limited to questionnaires, recalls, diaries, or digital health technologies (e.g., wearables, sensors, medical devices, apps). Though applicants cannot collect new data, they will be allowed to process existing raw data if proper scientific justification is provided. For example, if 24-hour actigraphy data were collected or available, researchers are permitted to analyze the raw data to create new summary output measures of the modifiable risk factor(s) of interest (e.g., sleep or physical activity).
Applications should consider best practices for analyzing the data, as well as both robust conceptual models for integration of these behaviors and statistical models for analysis. This also includes consideration of the sample size necessary for the proposed research question and modeling approach. All applications are required to discuss implicit methodological biases (e.g., algorithmic, computational) and plans to address it in the approach.
Resources developed through funded supplements, inclusive of datasets and related metadata as well as model algorithms and other code, are expected to be made publicly available and consistent with NIH Data Sharing Policies. All applications should include plans for sharing resources with the wider scientific community in a timely manner to enable other researchers to replicate and build on for future research efforts. Successful applicants may be required to participate in a workshop to disseminate findings.
Applications not responsive to this announcement include those that
- Propose work that was included in the original application;
- Propose non-human studies;
- Propose new, primary data collection of modifiable risk factors;
- Do not model three or more modifiable risk factors measured within a similar temporal window;
- Do not include scientific justification for analysis of modifiable risk factors outside a 24-hour temporal window;
- Provide a plan that is not reasonable for the proposed project to be completed, given the time and budget requested.
All applicants are encouraged to discuss their applications with the scientific/research contact listed below prior to submission.
Application and Submission Information
Applications for this initiative must be submitted using the following opportunity or its subsequent reissued equivalent.
- PA-20-272- Administrative Supplements to Existing NIH Grants and Cooperative Agreements (Parent Admin Supp Clinical Trial Optional)
All instructions in the SF424 (R&R) Application Guide and PA-20-272 must be followed, with the following additions:
- Application Due Date: Submissions must be received by June 6, 2025, at 5:00 p.m. local time of applicant organization for FY 2025 funding. The announcement will expire June 7, 2025.
- Applicants should begin the supplement application abstract by stating “This application is being submitted in response to "Administrative supplements for research leveraging novel data science approaches to address integration of modifiable risk factors on cancer outcomes".
- To facilitate efficient processing of the request, applicants are strongly encouraged to notify the assigned NCI program official for the parent award that a request has been submitted in response to this announcement.
Eligibility
- Only current awardees of an active NCI-funded R01, R37, R00, P01, P30, P50, U01, UM1, UH3, U19, and/or U54 are eligible to apply.
- PDs/PIs must hold an active award supported through NCI with sufficient time (minimum 1 year) left to complete the proposed project after the supplement has been awarded within the existing project period.
- Requests for no-cost extensions on the parent grant to accommodate a supplement will not be permitted.
- If an applicant anticipates a balance of 25% or more of the current total costs for the parent grant, please contact the scientific research contact prior to applying.
- Only one supplement application per parent award will be accepted for consideration. For supplements to parent awards that include multiple PDs/PIs, the supplement may be requested by any or all of the PDs/PIs (in accordance with the existing leadership plan) and submitted by the awardee institution of the parent award.
Page Limits
The application must include the following sections and adhere to the following limits:
- Project Summary/Abstract: 30 lines of text
- Project Narrative: 3 sentences
- Research Strategy: 5 pages
- Biographical Sketch: for Senior/Key Personnel and Significant Contributors only
Budget
- The budget should not exceed $100,000 in total costs for the entire allowable 1-year project period of the application/award.
- The administrative supplement application budget is limited to 1 year only.
- Administrative supplements may only be used to meet increased costs that are within the scope of the approved award but were unforeseen when the new or renewal application or grant progress report for non-competing continuation support was submitted; supplements designed to meet cost increases for unanticipated expenses within the original scope of the project will not be considered.
- Publication costs and costs for travel to scientific conferences would not be supported.
Review and Selection Process
NCI will conduct administrative reviews of applications and will support the most meritorious applications submitted for consideration, based upon availability of funds. Additionally, NCI program staff will evaluate applications using the following selection factors:
- Does the administrative supplement reasonably allow for the proposed project to be completed, given the time and budget requested?
- Are the proposed activities relevant to the parent grant and original work scope?
- Does the applicant demonstrate satisfactory progress towards achieving the aims of the parent grant, as appropriate to the current stage of the project?
- Do the results from the proposed project have the potential to provide new information on computational approaches that would advance understanding of the integrative role of modifiable risk factors on cancer outcomes?
Inquiries
Applicants are encouraged to discuss their application with the scientific/research contacts listed below prior to submission.
Scientific Contacts
Dana L. Wolff-Hughes, PhD
National Cancer Institute (NCI)
Telephone: 240-620-0673
Email: dana.wolff@nih.gov
Kirsten Herrick, PhD, MSc
National Cancer Institute (NCI)
Telephone: 240-276-5734
Email: kirsten.herrick@nih.gov
Financial/Grants Management Contact(s)
Crystal Wolfrey
National Cancer Institute (NCI)
Telephone: 240-276-6277
Email: crystal.wolfrey@nih.gov